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A Comparative Study on Different Edge Detection Techniques after Applying Noise Removal Techniques to An Image

Pulkit Panwar, Nidhi Gulati

Abstract


In digital image processing and computer vision, image segmentation plays an important part. image segmentation refers to the sub division of image into different parts on the basis of different factors like edges, region, etc. edge detection is the most important factor of object recognition in an image. but unwanted signals like noise in an image can affect and degrade the edge detection process in image segmentation. this paper aims at removing noise from images before segmentation and then compare the result of different edge detection techniques after segmentation.

 

Cite this Article
Pulkit Panwar, Nidhi Gulati. A Comparative Study on Different Edge Detection Techniques after Applying Noise Removal Techniques to An Image. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(2): 33–40p.


Keywords


Sobel, prewitt, roberts cross, LOG, canny, median filter, mean filter, salt and pepper noise, gaussian noise

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References


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